Dissolution kinetics of ulexite in acetic acid solutions

Ulexite is an important boron mineral used for the production of boron compounds. The aims of this study are to examine the dissolution kinetics of ulexite in acetic acid solutions, and to present an alternative process to produce boric acid. In order to investigate the dissolution kinetics of ulexite in acetic acid solutions, the concentration of solution, reaction temperature, solid-to-liquid ratio, and particle size were selected as experimental parameters. It was determined that the dissolution rate of ulexite increased with increasing solution concentration and temperature and decreasing particle size and solid-to-liquid ratio. The activation energy of the process was found to be 55.8 kJ/mol.     

The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system

Mode choice modeling is probably the most important element of transportation planning. It affects the general efficiency of travel and the allocation of resources. The development of mode choice models has recently witnessed significant advances in many fields, such as passenger and freight transport. A large number of mathematical models have been used to model the traveler’s choice of mode and destination and the shipper’s choice of mode, shipment size and supply market, among others. Such models are not only becoming almost intractable but also data intensive, difficult to calibrate and update, and intransferable. These models cover a wide range of mathematical complexity and accuracy. This paper describes a new approach to mode choice of intercity freight transport modeling using artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) models. The new approach combines the learning ability of artificial neural networks and the transparent nature of fuzzy logic. The approach is found to be highly adaptive and efficient in investigating non-linear relationships among different variables. The adaptive neuro-fuzzy inference system model is tested on the freight transport market in Turkey, Germany, France and Austria by using information on the freight flows and their attributes. The ANNs and ANFIS models are more successful in the representation of the non-linear behavior of mode choice of intercity freight transport compared to the classical models.     

Identification of EMG signals using discriminant analysis and SVM classifier

The electromyography (EMG) signal is a bioelectrical signal variation, generated in muscles during voluntary or involuntary muscle activities. The muscle activities such as contraction or relaxation are always controlled by the nervous system. The EMG signal is a complicated biomedical signal due to anatomical/physiological properties of the muscles and its noisy environment. In this paper, a classification technique is proposed to classify signals required for a prosperous arm prosthesis control by using surface EMG signals. This work uses recorded EMG signals generated by biceps and triceps muscles for four different movements. Each signal has one single pattern and it is essential to separate and classify these patterns properly. Discriminant analysis and support vector machine (SVM) classifier have been used to classify four different arm movement signals. Prior to classification, proper feature vectors are derived from the signal. The feature vectors are generated by using mean absolute value (MAV). These feature vectors are provided as inputs to the identification/classification system. Discriminant analysis using five different approaches, classification accuracy rates achieved from very good (98%) to poor (96%) by using 10-fold cross validation. SVM classifier gives a very good average accuracy rate (99%) for four movements with the classification error rate 1%. Correct classification rates of the applied techniques are very high which can be used to classify EMG signals for prosperous arm prosthesis control studies.     

Synthesis and electrochemical,in situ spectroelectrochemical,electrical and gas sensing properties of ball-type homo- and hetero-dinuclear phthalocyanines with four [1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]furan-7,10-diyl] bridges

The new mono-nuclear Fe^II 2 and ball-type homo-dinuclear Fe^II–Fe^II 3 phthalocyanines have been synthesized from the corresponding 4,4′-(1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]-furan-7,10-diyl)bis(oxy)diphthalonitrile 1 while ball-type hetero-dinuclear Fe^II–Co^II phthalocyanine 4 was synthesized from 2. The compounds have been characterized by elemental analysis, UV–vis, IR and MALDI-TOF-mass spectroscopies. The redox behaviours of the complexes were identified by controlled-potential coulometry, cyclic voltammetry and differential pulse voltammetry measurements on Pt in dimethylsulfoxide containing tetrabutylammonium perchlorate. The assignments of the redox processes and the understanding of the interactions between the metal phthalocyanine units in 3 and 4 were achieved by the combined evaluation of the voltammetric and in situ spectroelectrochemical outcomes. Complex 3 showed ring-based mixed-valence behaviour as a result of the considerable interaction between the phthalocyanine rings. On the other hand, the interactions between the two metal phthalocyanine units of 4 were found to be much weaker than those in 3. The potential application of molecular organic semiconductors needs the control adjustment of conductivity. Ac and dc conductivity measurements were performed with the applied external electric filed. At high frequency, the conduction follows the universal power law and conduction mechanism can be explained by classical hopping barriers mechanism for the system.     

GNSS positioning accuracy improvement based on surface meteorological parameters using artificial neural networks

With the ongoing development of global navigation satellite system (GNSS) technologies, user's dependence on these technologies has drastically risen. Ranging anywhere from industrial applications to agriculture or geodetic applications, the growing demand has stimulated the need for more sophisticated equipment with seamless accuracy. However, the signal received by a GNSS receiver has always faced the risk of contamination by many different sources of error, and this issue decreases the GNSS positioning accuracy. One of the most notable errors is the delay that occurs mainly in the troposphere layer, which mostly relies on the meteorological condition parameters. In this work, an artificial neural network (ANN)‐based mitigation technique in order to eliminate troposphere delay is presented. Our ANN model trained using the surface meteorological parameters, namely, temperature, humidity, wind speed, maximum wind direction, and pressure with the number of satellites achieved by a GNSS receiver. The result showed that ANN model successfully improved the position accuracy level of the GNSS receiver in both horizontal (2D) and three dimensions (3D) at 43.77% and 19.19%, respectively.     

Compensation of oxygen defects in La-silicate gate dielectrics for improving effective mobility in high-k/metal gate MOSFET using oxygen annealing process

Oxygen incorporation for compensation of oxygen defects is investigated with La-silicate dielectrics in directly contacted with the Si substrate. The amount of oxygen is controlled by the temperature of annealing in oxygen atmosphere (oxygen annealing) and the thickness of the gate electrode. The positive shift in flatband voltage (V_FB) by oxygen incorporation is an experimental evidence for defects compensation in La-silicate dielectrics. Optimum oxygen annealing provides the V_FB shift toward positive direction without increasing equivalent oxide thickness (EOT). Although the oxygen annealing degrades the interfacial property at La-silicate/Si interface, subsequent forming gas annealing (FGA) can recover the interfacial property. It is experimentally revealed that the positive V_FB shift of La-silicate dielectrics is stable even after subsequent FGA. The supplied oxygen in La-silicate is expected to maintain even after reducing process. Movement of Fermi level toward the Si valence band edge caused by oxygen incorporation is successfully observed by XPS. Moreover, no chemical reaction between La-silicate and Si substrate by oxygen annealing are confirmed from TEM observation and analyses of X-ray photoelectron spectra. It is experimentally demonstrated that effective hole mobility can be improved without increase in EOT by combination of oxygen annealing and FGA.